Cognitive Overload is the most frequently reported dimension of AI fatigue, driven by output volume and repeated verification¶
Claim · All claims
Evidence · 1 study · qualitativer2·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2031: baselines and conditions change
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? 310 participants reported mental strain from processing AI-generated outputs and performing repeated verification tasks, making Cognitive Overload the most prominent dimension. → Miranda 2026
Evidence¶
Miranda 2026¶
Miranda, J. P. P., Parreño, E. B., & Rivera, J. G. (2026). Defining AI Fatigue in Academic Contexts: Dimensions, Indicators, and a Stage-Based Model Using Grounded Theory. International Journal of Learning, Teaching and Educational Research, 25(5), 91–107. https://doi.org/10.26803/ijlter.25.5.5
q2 · i? · qualitative · r2
Frequency counts from grounded theory coding of 1,054 student responses. The Output Overwhelm and Verification Strain indicators captured difficulty handling AI response volume and exhaustion from repeated checking; e.g., "I feel mentally exhausted after checking so many outputs" (n = 72). No effect sizes are printed.
"Cognitive Overload was the most prominent dimension, with 310 participants reporting mental strain from processing AI -generated outputs and performing repeated verification tasks."
Discussion¶
Related Claims¶
- Physical Strain, reported by 120 participants, comprises visual fatigue and session exhaustion from reading and verifying AI outputs — related
- Grounded theory analysis of 1,054 university students identifies five dimensions of AI fatigue, each with two indicators — a broader claim this one bears on
- Students' top two concerns about educational LLM use are output quality (fabricated or misleading content, 53 mentions) and the verification burden (34 mentions) — related
- Moral Unease, reported by 190 participants, reflects authorship guilt and a gap between AI output quality and actual understanding — related
- First-year students report coexisting high approval of AI-enabled courses and high self-reported psychological strain, with strain indicators endorsed by more than two-thirds of the sample — a broader claim this one bears on
- AI output errors are frequent: 44.5% fabricated references in drafted research proposals and 5–13% unsafe chatbot medical answers — related
- Students used visualizations to verify their own reasoning rather than as primary explanation tools, valuing control over their cognitive effort (agency) — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
cognitive-overload-most-reported-ai-fatigue-dimension |
title |
Cognitive Overload is the most frequently reported dimension of AI fatigue, driven by output volume and repeated verification |
description |
Cognitive Overload is the most frequently reported dimension of AI fatigue, driven by output volume and repeated verification |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
recheck_by |
2031 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — miranda-2026 |
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